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Cloudwick Corrals Big Data

Many companies are turning to a new type of data service provider to manage the ever-increasing amounts of information generated by their daily operations. What are these service providers called? They are called Big Data as a Service (BDaaS) providers, and Cloudwick Amazon is one of the biggest.

It is no secret to anyone that the amount of data being collected by companies like Facebook and Twitter has experienced phenomenal growth. The name for all this information is Big Data, which is nothing more than bigger, more complex data sets often from new data sources. Think of the millions of users on a social media site for example and the vast amount of text, audio and video data generated by the posts and photographs they create every day. The amount of information these companies generate is truly staggering.

So what exactly does a BDaaS provider like Cloudwick Amazon do for these technological movers and shakers?

Simply put, BDaaS providers manage, process and analyze Big Data stored in the Cloud through Amazon Web Services. A helpful way to think of Cloudwick Amazon is to compare them to an architect. An architect creates a design for a structure built out of raw materials. Once the structure is completed, it provides many benefits to the owner. A Big Data as a service company designs a blue print and builds structure for raw data, including new kinds of data such as audio and video. This allows companies to easily and securely interpret the data to better understand their users. The insight gained by the analysis helps companies to grow and compete.

Currently Cloudwick Amazon manages over 50,000 Big Data clusters for Global 1000 companies on Amazon Web Services . These Big Data clusters are sometimes referred to as Data Lakes. One of the many benefits of employing Cloudwick Amazon is the experience that they have gained by creating and managing so many Data Lakes on Amazon Web Services. This experience has streamlined their methodology into 3 basic, repeatable steps when migrating large quantities of data to AWS.

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